Diane Larlus

According to our database, Diane Larlus authored at least 72 papers between 2005 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Geo4D: Leveraging Video Generators for Geometric 4D Scene Reconstruction.

Zeren Jiang, Chuanxia Zheng, Iro Laina, Diane Larlus, Andrea Vedaldi

CoRR, April, 2025

Lifelong Visual Representation Learning.

Diane Larlus

Proceedings of the 20th International Joint Conference on Computer Vision, 2025

Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos.

Vadim Tschernezki, Diane Larlus, Iro Laina, Andrea Vedaldi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

DUNE: Distilling a Universal Encoder from Heterogeneous 2D and 3D Teachers.

Mert Bülent Sariyildiz, Philippe Weinzaepfel, Thomas Lucas, Pau de Jorge, Diane Larlus, Yannis Kalantidis

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

On Good Practices for Task-Specific Distillation of Large Pretrained Visual Models.

Juliette Marrie, Michael Arbel, Julien Mairal, Diane Larlus

Trans. Mach. Learn. Res., 2024

LUDVIG: Learning-free Uplifting of 2D Visual features to Gaussian Splatting scenes.

Juliette Marrie, Romain Menegaux, Michael Arbel, Diane Larlus, Julien Mairal

CoRR, 2024

On Good Practices for Task-Specific Distillation of Large Pretrained Models.

Juliette Marrie, Michael Arbel, Julien Mairal, Diane Larlus

CoRR, 2024

Weatherproofing Retrieval for Localization with Generative AI and Geometric Consistency.

Yannis Kalantidis, Mert Bülent Sariyildiz, Rafael S. Rezende, Philippe Weinzaepfel, Diane Larlus, Gabriela Csurka

Proceedings of the Twelfth International Conference on Learning Representations, 2024

UNIC: Universal Classification Models via Multi-teacher Distillation.

Mert Bülent Sariyildiz, Philippe Weinzaepfel, Thomas Lucas, Diane Larlus, Yannis Kalantidis

Proceedings of the Computer Vision - ECCV 2024, 2024

What Could Go Wrong? Discovering and Describing Failure Modes in Computer Vision.

Gabriela Csurka, Tyler L. Hayes, Diane Larlus, Riccardo Volpi

Proceedings of the Computer Vision - ECCV 2024 Workshops, 2024

PANDAS: Prototype-based Novel Class Discovery and Detection.

Tyler L. Hayes, César Roberto de Souza, Namil Kim, Jiwon Kim, Riccardo Volpi, Diane Larlus

Proceedings of the Conference on Lifelong Learning Agents, 2024

2023

EPIC Fields: Marrying 3D Geometry and Video Understanding.

Vadim Tschernezki, Ahmad Darkhalil, Zhifan Zhu, David Fouhey, Iro Laina, Diane Larlus, Dima Damen, Andrea Vedaldi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

No Reason for No Supervision: Improved Generalization in Supervised Models.

Mert Bülent Sariyildiz, Yannis Kalantidis, Karteek Alahari, Diane Larlus

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Fake it Till You Make it: Learning Transferable Representations from Synthetic ImageNet Clones.

Mert Bülent Sariyildiz, Karteek Alahari, Diane Larlus, Yannis Kalantidis

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

SLACK: Stable Learning of Augmentations with Cold-Start and KL Regularization.

Juliette Marrie, Michael Arbel, Diane Larlus, Julien Mairal

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

RaSP: Relation-aware Semantic Prior for Weakly Supervised Incremental Segmentation.

Subhankar Roy, Riccardo Volpi, Gabriela Csurka, Diane Larlus

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

TLDR: Twin Learning for Dimensionality Reduction.

Yannis Kalantidis, Carlos Eduardo Rosar Kós Lassance, Jon Almazán, Diane Larlus

Trans. Mach. Learn. Res., 2022

Fake it till you make it: Learning(s) from a synthetic ImageNet clone.

Mert Bülent Sariyildiz, Karteek Alahari, Diane Larlus, Yannis Kalantidis

CoRR, 2022

Improving the Generalization of Supervised Models.

Mert Bülent Sariyildiz, Yannis Kalantidis, Karteek Alahari, Diane Larlus

CoRR, 2022

Learning Super-Features for Image Retrieval.

Philippe Weinzaepfel, Thomas Lucas, Diane Larlus, Yannis Kalantidis

Proceedings of the Tenth International Conference on Learning Representations, 2022

ARTEMIS: Attention-based Retrieval with Text-Explicit Matching and Implicit Similarity.

Ginger Delmas, Rafael Sampaio de Rezende, Gabriela Csurka, Diane Larlus

Proceedings of the Tenth International Conference on Learning Representations, 2022

Granularity-Aware Adaptation for Image Retrieval Over Multiple Tasks.

Jon Almazán, ByungSoo Ko, Geonmo Gu, Diane Larlus, Yannis Kalantidis

Proceedings of the Computer Vision - ECCV 2022, 2022

On the Road to Online Adaptation for Semantic Image Segmentation.

Riccardo Volpi, Pau de Jorge, Diane Larlus, Gabriela Csurka

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Neural Feature Fusion Fields: 3D Distillation of Self-Supervised 2D Image Representations.

Vadim Tschernezki, Iro Laina, Diane Larlus, Andrea Vedaldi

Proceedings of the International Conference on 3D Vision, 2022

2021

Domain Adaptation in Multi-View Embedding for Cross-Modal Video Retrieval.

Jonathan Munro, Michael Wray, Diane Larlus, Gabriela Csurka, Dima Damen

CoRR, 2021

StacMR: Scene-Text Aware Cross-Modal Retrieval.

Andrés Mafla, Rafael Sampaio de Rezende, Lluís Gómez, Diane Larlus, Dimosthenis Karatzas

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Unsupervised Meta-Domain Adaptation for Fashion Retrieval.

Vivek Sharma, Naila Murray, Diane Larlus, M. Saquib Sarfraz, Rainer Stiefelhagen, Gabriela Csurka

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Concept Generalization in Visual Representation Learning.

Mert Bülent Sariyildiz, Yannis Kalantidis, Diane Larlus, Karteek Alahari

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Continual Adaptation of Visual Representations via Domain Randomization and Meta-Learning.

Riccardo Volpi, Diane Larlus, Grégory Rogez

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Probabilistic Embeddings for Cross-Modal Retrieval.

Sanghyuk Chun, Seong Joon Oh, Rafael Sampaio de Rezende, Yannis Kalantidis, Diane Larlus

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

NeuralDiff: Segmenting 3D objects that move in egocentric videos.

Vadim Tschernezki, Diane Larlus, Andrea Vedaldi

Proceedings of the International Conference on 3D Vision, 2021

2020

Capturing the Geometry of Object Categories from Video Supervision.

David Novotný, Diane Larlus, Andrea Vedaldi

IEEE Trans. Pattern Anal. Mach. Intell., 2020

Hard Negative Mixing for Contrastive Learning.

Yannis Kalantidis, Mert Bülent Sariyildiz, Noé Pion, Philippe Weinzaepfel, Diane Larlus

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Visual Representations with Caption Annotations.

Mert Bülent Sariyildiz, Julien Perez, Diane Larlus

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings.

Michael Wray, Gabriela Csurka, Diane Larlus, Dima Damen

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

Re-ID done right: towards good practices for person re-identification.

Jon Almazán, Bojana Gajic, Naila Murray, Diane Larlus

CoRR, 2018

Semi-convolutional Operators for Instance Segmentation.

David Novotný, Samuel Albanie, Diane Larlus, Andrea Vedaldi

Proceedings of the Computer Vision - ECCV 2018, 2018

Self-Supervised Learning of Geometrically Stable Features Through Probabilistic Introspection.

David Novotný, Samuel Albanie, Diane Larlus, Andrea Vedaldi

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Generalizing Semantic Part Detectors Across Domains.

David Novotný, Diane Larlus, Andrea Vedaldi

Proceedings of the Domain Adaptation in Computer Vision Applications., 2017

End-to-End Learning of Deep Visual Representations for Image Retrieval.

Albert Gordo, Jon Almazán, Jérôme Revaud, Diane Larlus

Int. J. Comput. Vis., 2017

Learning 3D Object Categories by Looking Around Them.

David Novotný, Diane Larlus, Andrea Vedaldi

Proceedings of the IEEE International Conference on Computer Vision, 2017

AnchorNet: A Weakly Supervised Network to Learn Geometry-Sensitive Features for Semantic Matching.

David Novotný, Diane Larlus, Andrea Vedaldi

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Beyond Instance-Level Image Retrieval: Leveraging Captions to Learn a Global Visual Representation for Semantic Retrieval.

Albert Gordo, Diane Larlus

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Data-Driven Detection of Prominent Objects.

José A. Rodríguez-Serrano, Diane Larlus, Zhenwen Dai

IEEE Trans. Pattern Anal. Mach. Intell., 2016

Learning the semantic structure of objects from Web supervision.

David Novotný, Diane Larlus, Andrea Vedaldi

CoRR, 2016

What is the right way to represent document images?

Gabriela Csurka, Diane Larlus, Albert Gordo, Jon Almazán

CoRR, 2016

Learning the Structure of Objects from Web Supervision.

David Novotný, Diane Larlus, Andrea Vedaldi

Proceedings of the Computer Vision - ECCV 2016 Workshops, 2016

Deep Image Retrieval: Learning Global Representations for Image Search.

Albert Gordo, Jon Almazán, Jérôme Revaud, Diane Larlus

Proceedings of the Computer Vision - ECCV 2016, 2016

I Have Seen Enough: Transferring Parts Across Categories.

David Novotný, Diane Larlus, Andrea Vedaldi

Proceedings of the British Machine Vision Conference 2016, 2016

2015

Understanding the Fisher Vector: a multimodal part model.

David Novotný, Diane Larlus, Florent Perronnin, Andrea Vedaldi

CoRR, 2015

Fisher vectors meet Neural Networks: A hybrid classification architecture.

Florent Perronnin, Diane Larlus

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

What makes an Image Iconic? A Fine-Grained Case Study.

Yangmuzi Zhang, Diane Larlus, Florent Perronnin

CoRR, 2014

Incorporating Near-Infrared Information into Semantic Image Segmentation.

Neda Salamati, Diane Larlus, Gabriela Csurka, Sabine Süsstrunk

CoRR, 2014

2013

Predicting an Object Location Using a Global Image Representation.

José A. Rodríguez-Serrano, Diane Larlus

Proceedings of the IEEE International Conference on Computer Vision, 2013

What is a good evaluation measure for semantic segmentation?.

Gabriela Csurka, Diane Larlus, Florent Perronnin

Proceedings of the British Machine Vision Conference, 2013

2012

On the use of regions for semantic image segmentation.

Rui Hu, Diane Larlus, Gabriela Csurka

Proceedings of the Eighth Indian Conference on Vision, Graphics and Image Processing, 2012

Semantic Image Segmentation Using Visible and Near-Infrared Channels.

Neda Salamati, Diane Larlus, Gabriela Csurka, Sabine Süsstrunk

Proceedings of the Computer Vision - ECCV 2012. Workshops and Demonstrations, 2012

2011

Weakly Supervised Recognition of Daily Life Activities with Wearable Sensors.

Maja Stikic, Diane Larlus, Sandra Ebert, Bernt Schiele

IEEE Trans. Pattern Anal. Mach. Intell., 2011

Assessing the aesthetic quality of photographs using generic image descriptors.

Luca Marchesotti, Florent Perronnin, Diane Larlus, Gabriela Csurka

Proceedings of the IEEE International Conference on Computer Vision, 2011

Combining Visible and Near-Infrared Cues for image Categorisation.

Neda Salamati, Diane Larlus, Gabriela Csurka

Proceedings of the British Machine Vision Conference, 2011

2010

Manifold Based Local Classifiers: Linear and Nonlinear Approaches.

Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill Triggs, Frédéric Jurie

J. Signal Process. Syst., 2010

Category Level Object Segmentation by Combining Bag-of-Words Models with Dirichlet Processes and Random Fields.

Diane Larlus, Jakob Verbeek, Frédéric Jurie

Int. J. Comput. Vis., 2010

Extracting Structures in Image Collections for Object Recognition.

Sandra Ebert, Diane Larlus, Bernt Schiele

Proceedings of the Computer Vision, 2010

2009

Learning Color Names for Real-World Applications.

Joost van de Weijer, Cordelia Schmid, Jakob Verbeek, Diane Larlus

IEEE Trans. Image Process., 2009

Latent mixture vocabularies for object categorization and segmentation.

Diane Larlus, Frédéric Jurie

Image Vis. Comput., 2009

Multi-graph Based Semi-supervised Learning for Activity Recognition.

Maja Stikic, Diane Larlus, Bernt Schiele

Proceedings of the 13th IEEE International Symposium on Wearable Computers (ISWC 2009), 2009

2008

Création et utilisation de vocabulaires visuels pour la catégorisation d'images et la segmentation de classes d'objets. (Creating and using visual vocabularies for image categorization and object class segmentation).

Diane Larlus

PhD thesis, 2008

Combining appearance models and Markov Random Fields for category level object segmentation.

Diane Larlus, Frédéric Jurie

Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

2007

Category level object segmentation - learning to segment objects with latent aspect models.

Diane Larlus, Frédéric Jurie

Proceedings of the VISAPP 2007: Proceedings of the Second International Conference on Computer Vision Theory and Applications, Barcelona, Spain, March 8-11, 2007, 2007

Towards autonomous object reconstruction for visual search by the humanoid robot HRP-2.

Olivier Stasse, Diane Larlus, Baptiste Lagarde, Adrien Escande, François Saïdi, Abderrahmane Kheddar, Kazuhito Yokoi, Frédéric Jurie

Proceedings of the 2007 7th IEEE-RAS International Conference on Humanoid Robots, November 29th, 2007

2006

Latent Mixture Vocabularies for Object Categorization.

Diane Larlus, Frédéric Jurie

Proceedings of the British Machine Vision Conference 2006, 2006

2005

The 2005 PASCAL Visual Object Classes Challenge.

Mark Everingham, Andrew Zisserman, Christopher K. I. Williams, Luc Van Gool, Moray Allan, Christopher M. Bishop, Olivier Chapelle, Navneet Dalal, Thomas Deselaers, Gyuri Dorkó, Stefan Duffner, Jan Eichhorn, Jason D. R. Farquhar, Mario Fritz, Christophe Garcia, Tom Griffiths, Frédéric Jurie, Daniel Keysers, Markus Koskela, Jorma Laaksonen, Diane Larlus, Bastian Leibe, Hongying Meng, Hermann Ney, Bernt Schiele, Cordelia Schmid, Edgar Seemann, John Shawe-Taylor, Amos J. Storkey, Sándor Szedmák, Bill Triggs, Ilkay Ulusoy, Ville Viitaniemi, Jianguo Zhang

Proceedings of the Machine Learning Challenges, 2005